In many digital communication systems, a source generates digital information, such as data, audio, or video, that is to be transmitted to multiple receivers. The digital information bits are divided into blocks that define a discrete alphabet of symbols. These symbols are used to modulate a radio frequency (RF) carrier's frequency, amplitude and/or phase. For example, a quadrature oscillator can be used to modulate the symbols onto the amplitude and phase of the RF carrier, and the signaling is referred to as Quadrature Amplitude Modulation (QAM). The time between adjacent symbols is referred to as the baud (or symbol) period, and inverse as baud (or symbol) rate.
The data-bearing RF carrier is amplified and transmitted through a propagation medium, for example, a cable, phone line, wireless terrestrial, satellite, underwater link, etc. As consumer appetite for information on demand continues to increase, so do requirements on data rates of present and emerging systems. Higher data rates increase the susceptibility of the data-bearing RF signal to environment-induced distortions such as fades, multipath (causing inter-symbol interference (ISI)), Doppler conditions, and additive noise processes. Communications receivers typically implement multiple stages of signal processing to individually address impairments witnessed by the RF signal en route to the receiver, and also introduced by the receiver and transmitter themselves, for example, due to implementation with finite-length filters and finite-precision arithmetic. Typical functions that govern physical layer operation include equalization, synchronization to carrier phase and frequency, synchronization to baud sampling phase and frequency, and automatic gain control.
Gain control processing adjusts the received signal to within the proper dynamic range expected by the receiver. Usually, gain control is itself done in stages, for example, at the RF level by the tuner, after RF to IF translation, and digitally within front-end and back-end signal processing. Most commercial UHF/VHF tuners include automatic gain control (AGC) circuits that tradeoff performance between adjacent and co-channel interference using average or peak power levels. AGC at the IF level usually adjusts the signal so that the full dynamic range of analog-to-digital conversion is utilized, without saturation. Sometimes, AGC utilizes pilot or reference tones or signals that are known, stored, or derived in the receiver to adjust IF AGC circuitry. In the digital domain, AGC circuitry may also use pilot or reference aids, or may operate blindly without the use of such overheard. For example, U.S. Ser. No. 60/341,931, entitled “Self-initializing decision feedback equalizer with automatic gain control,” by T. J. Endres et al., filed Dec. 17, 2001, which is incorporated herein by this reference, describes an automatic gain control (AGC) circuit that is nested with a decision feedback equalizer (DFE) structure, which operates on novel error signals that are blind (do not use training, reference, or pilot aids). Similarly, U.S. Ser. No. 10/246,084, entitled, “Adaptive expanded information capacity for communications systems,” by C. Long et al., filed Sep. 8, 2002, which is incorporated herein by reference, describes a similar feedback AGC circuit that is nested with an equalizer and uses decision-directed (DD) error adjustment.
Timing recovery refers to the process of synchronization to correct baud sampling frequency and phase. Sometimes, the oscillator clock that adjusts the analog-to-digital converter (ADC) at the input to the receiver is adjusted in frequency and phase. Alternatively, the sampled data in the receiver can be interpolated to achieve proper baud sampling. This second approach can reduce complexity by eliminating costly oscillator circuitry needed to control the ADC in the first approach. Timing recovery methods sometimes try to detect zero-crossings of the received signal in the time domain. As such, some methods apply filtering techniques to upper and lower band edges of the data spectrum. For example, see U.S. Pat. No. 5,872,815 by C. Strolle et al, entitled “Apparatus for generating timing signals for a digital receiver” which is incorporated by this reference. Alternatively, another approach uses a decision-directed (DD) technique, usually requiring feedback from a decision device, or slicer, or quantizer. The DD methods described by Mueller and Muller in “Timing recovery in digital synchronous data receivers,” IEEE Transactions on Communications, vol. COM-24, no. 5, May 1976, which is incorporated by this reference, are widely applied. Other blind algorithms, usually applied solely to equalization, have lately been successfully applied to timing recovery, too. For example, Guglielmi et al. in “Joint Clock Recovery and Baseband Combining for the Diversity Radio Channel,” IEEE Transactions on Communications, vol. 44. p. 114-117, January 1996, which is incorporated by this reference, jointly applies a Constant Modulus Algorithm (CMA), originally proposed by D. N. Godard in “Self-recovering equalization in two-dimensional data communication systems,” IEEE Transactions on Communications, vol. 28, no. 11, pp. 1867-1875, October 1980, which is also incorporated by this reference, for equalization, to joint optimization of equalization and timing recovery. This joint optimization is further analyzed by Chung et al. in “Timing Recovery Based on Dispersion Minimization,” Proceedings of the 2001 Conference on Information Sciences and Systems, March 2001 which is incorporated by reference.
Equalization in a digital communications receiver is analogous to an equalizer on a stereo system: the equalizer filters the distorted, received waveform (from a tape head or RF antenna) and tries to mitigate distortions and restore the signal properties of the original source. In a digital communications receiver, filter mismatches in transmitter and receiver, finite-precision implementation, and propagation channel effects induce inter-symbol interference (ISI), in which the receiver processes a signal that contains multiple, delayed and weighted copies of the transmitted signal. For example, reflections of the RF signal from a large building will induce ISI (or multipath), and reflections from an airplane will induce multipath distortion with a time-varying Doppler component. Since the exact channel characteristics are not known apriori at the receiver, the equalizer is usually implemented with adaptive methods. Adjustment of filter coefficients can be done with trained equalization methods, relying on the embedding of a pre-determined training sequence in the transmitted data. Usually, equalizer coefficient convergence relies on multiple transmissions of the training sequence, and the channel characteristics are also time varying, requiring periodic re-training. The Least Mean Squares (LMS) algorithm, which was proposed by Widrow, McCool, and Ball, in The Proceedings of the IEEE, vol. 63, no. 4, pp. 719-720, April 1975, which is incorporated by reference, minimizes a Mean Squared Error (MSE) cost function and is a stochastic gradient descent update rule utilizing the training sequence. Alternatively, blind methods do not rely on a reference signal, or derive a reference signal from the data itself, and are therefore desirable, since in the absence of a training signal, revenue-generating user data can instead be transmitted. A common blind equalization method replaces the reference signal in the LMS algorithm with the receiver's best guess at the data, and is referred to as Decision Directed LMS (DD-LMS), as proposed in a paper entitled “Techniques for adaptive equalization of digital communication systems,” by R. W. Lucky, in the Bell Systems Technical Journal, vol. 45, no. 2, pp. 255-286, February 1966 which is incorporated by reference. Unfortunately, DD-LMS needs a reasonably low percentage of incorrect decisions to prevent algorithm divergence, and is therefore impractical from a cold-start initialization. Godard's CMA is an attractive alternative that provides robust signal acquisition in harsh environments. These algorithms are sometimes applied to linear, finite-impulse response (FIR) filters, or decision feedback equalizer (DFE) structures, in which an FIR filter is embedded in a feedback loop (so that the overall impulse response is infinite) that processes hard decision samples from a decision device, slicer, or quantizer. U.S. Ser. No. 60/341,931 by T. J. Endres et al. entitled “Self-initializing decision feedback equalizer with automatic gain control,” which is incorporated by reference, uses novel, adaptive combining techniques of soft and hard decision samples in a DFE structure with CMA, LMS, and DD-LMS for robust, blind acquisition and re-acquisition.
Synchronization to carrier frequency and phase is usually done in stages, including, for example, RF to IF translation, IF to passband (or near baseband), and translation to precise baseband. Since the receiver in a coherent communications system must ultimately make hard decisions for symbol estimates, the data-bearing RF signal must ultimately be brought down to precise baseband. Synchronous or quasi-synchronous detectors can be used for intermediate translations. Translation to precise baseband can be done in a DD fashion, by nesting a phase-locked loop with the slicer and equalizer. For example, the instantaneous phase offset between slicer input and output is detected, filtered, and used to drive an oscillator in “Digital Communication” by E. A. Lee and D. G. Messerschmitt, Kluwer Academic Publishers, 1994, which is incorporated by reference. The PLL can be closed at various points within the equalizer. For example, Strolle et al describe alternative DFE architectures for reception of digital television signals that include a DD carrier loop, deriving its input from slicer input and output, but derotating the received signal to precise baseband at various points within the DFE structure. (See: Feasibility of reliable 8-VSB reception,” C. H. Strolle, S. N. Hulyalkar, T. J. Endres, Proceedings of the NAB Broadcast Engineering Conference, Las Vegas, Nev., pp. 483-488, Apr. 8-13, 2000, which is incorporated by reference.)
The present invention relates to the joint, adaptive, control of physical layer functions that govern equalization, baseband synchronization to precise carrier phase and frequency, baud sampling phase and frequency, and automatic gain control in the digital domain.